POPULATION AGEING AND WELFARE DISSIMILARITIES WITHIN THE EUROPEAN UNION: A NEW APPROACH BASED ON CLUSTER ANALYSIS
POPULATION AGEING AND WELFARE DISSIMILARITIES WITHIN THE EUROPEAN UNION: A NEW APPROACH BASED ON CLUSTER ANALYSIS
Author(s): Mirela Cristea, Grațiela Georgiana Noja, Yannis ThalassinosSubject(s): Economy, Socio-Economic Research
Published by: Универзитет у Нишу
Keywords: labour market; economic development; demographic economics; cluster analysis
Summary/Abstract: The research aims to identify several dissimilarities between the European Union Member States (EU-27 MS) in terms of welfare and labour market dimensions under the sheer implications of the ageing phenomenon. The quantitative research methodology emphasizes the cluster analysis based on the Ward method, performed for the year 2018. Main results denote that only two countries (Denmark and Sweden) registered soaring performances, especially for the labour market credentials (particularly the employment rate and active policies). Other 10 EU-27 MS accounted medium performances in terms of well-being, but also the lowest achievements as regards the old dependency rate, the employment rate of persons aged 55-64 and the birth rate. This paper brings to the fore the keen need to redesign specific policies and tailored strategies by the responsible authorities and business representatives across the EU, in order to enhance achievements and new solutions for the difficulties brought by population ageing, with spillover effects on the labour market integration of older employees and overall economic welfare. The study stands out through the new integrative approach based on cluster analysis that underlines the dissimilarities between the EU member states, and the features of each group of countries, in a pre-settled framework, thus grasping the difficulties, but also the opportunities faced in terms of ageing and economic welfare.
Journal: FACTA UNIVERSITATIS - Economics and Organization
- Issue Year: 18/2021
- Issue No: 1
- Page Range: 17-27
- Page Count: 11
- Language: English